Combining Spectral with Texture Features into Objectoriented Classification in Mountainous Terrain Using Advanced Land Observing Satellite Image  

作　　者：LIU En-qin ZHOU Wan-cun ZHOU Jie-ming SHAO Huai-yong YANG Xin 

机构地区：[1]Key Laboratory of Geo-special Information Technology,Ministry of Land and Resources,Chengdu University of Technology [2]Chengdu Institute of Mountain Hazards and Environment,Chinese Academy of Sciences [3]University of Chinese Academy of Sciences [4]The Faculty of Geography Resources Scienses,Sichuan Normal University

出　　处：《Journal of Mountain Science》2013年第5期768-776,共9页山地科学学报（英文）

基　　金：supported jointly by Key Laboratory of Geo-special Information Technology, Ministry of Land and Resources (Grant No. KLGSIT2013-12);Knowledge Innovation Program (Grant No. KSCX1-YW-09-01) of Chinese Academy of Sciences

摘　　要：Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures （such as shadow）. At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM （Gray Level Co- occurrence Matrix） were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification （MLC）. Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and o.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.

关 键 词：Texture features Object-orientedclassification Land use MOUNTAIN ALOS 

分 类 号：P228[天文地球—大地测量学与测量工程] P931[天文地球—测绘科学与技术]